IP Library Granted Patent US 11,550,299
Granted Patent B2
US 11,550,299 · App. 17/332,700 · Granted Jan 10, 2023

Automated robotic process selection and configuration

Inventors: Charles Howard Cella (Pembroke, MA); Jenna Lynn Parenti (Boulder, CO); Taylor D. Charon (Troy, MI)
Assignee: Strong Force TX Portfolio 2018, LLC
G05B19/4155B25J9/161B25J9/163B25J9/1656B25J13/00G05B13/027G05B19/18G06F3/015G06F9/466G06F9/543G06F16/2379G06F16/27G06K9/6215G06K9/6218G06K9/6268G06N3/0427G06N3/0454G06N3/08G06N5/04G06N20/00G06Q10/0639G06Q10/10G06Q20/405G06Q30/018G06Q30/0201G06Q30/0206G06Q30/0208G06Q30/0215G06Q30/0278G06Q40/025G06Q40/08G06Q50/01G06Q50/18G06Q50/188G06Q50/26G16Y10/50G16Y40/10H04L9/0637G05B2219/39292G05B2219/50391G06Q40/04G06Q2220/18
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Quick Facts
Patent No.
US 11,550,299
App. No.
17/332,700
Granted
Jan 10, 2023
Kind
B2
Abstract

A system for selection and configuration of an automated robotic process includes a media input module structured to receive at least one functional media, a media analysis module structured to analyze the at least one functional media and identify an action parameter; and a solution selection module structured to select at least one component of an AI solution for use in an automated robotic process, wherein the selection is based, at least in part, on the action parameter.

Claims (36)

1. A system for selection and configuration of an automated robotic process, the system comprising:

a processor;

a media input module operably coupled to the processor and structured to receive at least one functional media, the at least one functional media comprising a media indicative of brain activity in a human engaged in a task of interest, the brain activity comprising:

a set of spatial-temporal neocortical activity patterns of the human; and

information of an active area of a neocortex of the human;

a media analysis module structured to:

analyze the at least one functional media;

identify an action parameter of the human, based on the brain activity from the analyzed at least one functional media; and

identify an activity level in at least one brain region of the human from the analyzed at least one functional media; and

provide a brain region parameter of the human from the analyzed at least one functional media, corresponding with the activity level in the at least one brain region, corresponding to a region of the neocortex comprising one or more of frontal, parietal, occipital, or temporal lobes of the neocortex; a primary visual cortex; a primary auditory cortex; subdivisions of the neocortex; a ventrolateral prefrontal cortex; a Broca's area; or an orbitofrontal cortex; and

a solution selection module structured to select at least one component of an AI solution for use in an automated robotic process,

wherein the selection is based, at least in part, on the identified action parameter to simulate the action parameter of the human,

wherein the at least one selected component of the AI solution simulates a processing activity similar to the activity of the brain region of the human indicated by the brain region parameter, and

wherein the at least one component of the AI solution corresponds to the set of spatial-temporal neocortical activity patterns of the human.

2. The system of claim 1 , wherein the solution selection module is further structured to select the at least one component of the AI solution based, at least in part, on the brain region parameter.

3. The system of claim 1 , wherein:

the media analysis module is further structured to provide an activity parameter that relates to the human engaged task of interest and corresponds with the brain region parameter; and

the solution selection module is further structured to select at least one component of the AI solution based, at least in part, on the activity parameter.

4. The system of claim 3 , wherein the activity parameter includes at least one of “engaged”, “unengaged”, a level of activity, or a type of activity.

5. The system of claim 3 , further comprising a component configuration module structured to set a configuration parameter based on, at least in part, at least one of the activity parameter or the brain region parameter.

6. The system of claim 1 , wherein the solution selection module is further structured to identify a runtime input based, at least in part, on the brain region parameter.

7. The system of claim 1 , wherein the brain region parameter is indicative of a neocortex region including at least one of Fp 1 , F 7 , F 3 , T 3 , C 3 , T 5 , P 3 , O 1 , Fp 2 , F 8 , F 4 , T 4 , C 4 , T 6 , P 4 , or O 2 .

8. The system of claim 3 , wherein the activity parameter is representative of an activity including at least one of visual processing, inductive reasoning, auditory processing, olfactory processing, muscle control, looking, listening, smelling, motion activity, listening to sound of equipment, or watching another negotiator.

9. The system of claim 8 , wherein, when the activity parameter is representative of the olfactory processing, an input specification module is further structured to identify at least one chemical sensor as a robotic input.

10. The system of claim 8 , wherein, when the activity parameter is representative of the visual processing, an input specification module is further structured to identify at least one visual sensor as a robotic input.

11. The system of claim 10 , wherein a sensitivity of the at least one visual sensor comprises a portion of a range of wavelengths between about 380 to about 700 nanometers.

12. The system of claim 8 , wherein, when the activity parameter is representative of the auditory processing, an input specification module is further structured to identify at least one microphone as a robotic input.

13. The system of claim 1 , wherein the media analysis module is further structured to identify a second brain region parameter.

14. The system of claim 13 , wherein the second brain region parameter is indicative of at least one of: a resolution of the at least one functional media, a strength of an engagement signal, a relative strength of an engagement signal between the brain region parameter and the second brain region parameter, or an extent of a brain region engagement.

15. The system of claim 1 , wherein the selected at least one component of the AI solution includes at least one of a model, an expert system, a type of neural network, a specific machine-learning algorithm, a configuration specification, a specified input, a specified output, a learning parameter, a change rate, a weighting, or a threshold.

16. The system of claim 1 , wherein:

the at least one functional media comprises a video feed of the human engaged in the task of interest; and

the action parameter is representative of an action including at least one of listening, looking, smelling, or touching.

17. The system of claim 1 , wherein:

the action parameter comprises an ordered series of actions; and

the solution selection module is further structured to select a plurality of components for the AI solution, the selection is based, at least in part, on the ordered series of actions.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 13, 2022
From: CELLA, CHARLES HOWARD; PARENTI, JENNA LYNN; CHARON, TAYLOR D.
To: STRONG FORCE TX PORTFOLIO 2018, LLC
Reel/Frame 058652/0691 →
Continuity (6)
Continuation PCTUS2021016473 · Feb 3, 2021
Continuation In Part 16780519 · Feb 3, 2020
Provisional Application 63127980 · Dec 18, 2020
Provisional Application 63069542 · Aug 24, 2020
Provisional Application 62994581 · Mar 25, 2020
Related Publication 20210358032A1 · Nov 18, 2021
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